Ensemble Methods: Foundations and Algorithms - Zhi-Hua Zhou
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Piegāde 17-23 darba dienu laikā
30 dienu atgriešanas politika
Ensemble methods that train multiple learners and then combine them to use, with \textit{Boosting} and \textit{Bagging} as representatives, are well-known machine learning approaches. An ensemble is significantly more accurate than a single learner, and ensemble methods have already achieved great success in various real-world tasks.
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Aprašymas
Ensemble methods that train multiple learners and then combine them to use, with \textit{Boosting} and \textit{Bagging} as representatives, are well-known machine learning approaches. An ensemble is significantly more accurate than a single learner, and ensemble methods have already achieved great success in various real-world tasks.
Vairāk informācijas
| Autors | Zhi-Hua Zhou |
|---|---|
| Izdevējs | Taylor & Francis Ltd |
| Izlaides gads | 2025 |
| Vāka tips | Cietais vāks |
| EAN | 9781032960609 |